Generating and presenting targeted advertisements including representations of subject individuals

ABSTRACT

Advertisements are generated and selected for display to users, wherein the advertisements include representations of subject individuals. These subject individuals can be friends with whom the user interacts on the Internet and/or any other contributors who may or may not have expertise with regard to the subject matter of the advertisement. A subject individual can be portrayed in an advertisement by including any type of representation of the individual. 
     Ranks for the subject individuals are determined based on the subject individuals&#39; interactions with advertisements and/or on other factors. An advertisement is selected and presented to a user based on a score derived from friends&#39; and/or contributors&#39; interactions with the advertisement. According to various embodiments of the invention, a method is provided for choosing which advertisement(s) to show to a user and which subject individuals to portray in the advertisements.

CROSS-REFERENCES TO RELATED APPLICATIONS

This application claims priority from U.S. Provisional Application Ser.No. 61/031,692, for “Targeting Advertising Using Data Captured by SocialNetworks”, filed on Feb. 26, 2008, which is incorporated herein byreference.

This application is related to U.S. Utility patent application Ser. No.12/277,237 for “Ranking Interactions Between Users on the Internet”,filed Nov. 24, 2008, which is incorporated herein by reference.

FIELD OF ART

The present disclosure is directed to generating and presenting targetedadvertisements to users of the web, wherein such advertisements includerepresentations of subject individuals.

DESCRIPTION OF RELATED ART

With the changing trend in the use of World Wide Web technology thataims to enhance creativity, information sharing, and, most notably,collaboration among users, there has been an evolution of web-basedcommunities and hosted services in the form of social media. “Socialmedia” is an umbrella term for activities that enable people tointerlink and interact with engaging content in a conversational andparticipatory manner via the Internet. In essence, social media is usedto describe how people socialize or interact with each other throughoutthe World Wide Web.

Social media includes, for example, social networks where users buildprofiles and friend lists, photo sharing websites, instant messagingapplications, web-based email, retail sites where users can share wishlists, wedding planning sites that allow users to create personalizedpages to share information about a wedding with guests, and combinationsof several of these. Some social media, including social networks, havecreated open platforms so that external developers can writeapplications that use data captured by social media. Often, theseapplications correspond to advertising applications that provide formonetization of social media.

Advertising on the Internet generally attempts to maximize the effectivecost per thousand impressions (eCPM). eCPM is a well-known measurementof advertising effectiveness that indicates how much each thousand unitsof an advertisement inventory costs an advertiser. The ranks ofadvertisements are computed by multiplying bid eCPM's by user scores(also referred to as quality scores). The advertisements with thehighest ad rank are given preferential treatment. In the case ofadvertising opportunities where only one advertisement is displayed,preferential treatment means higher-ranked advertisements are displayedmore often than lower-ranked advertisements. In a situation wheremultiple advertisements are displayed, preferential treatment means theadvertisement is displayed more prominently than the others.

SUMMARY

According to various embodiments of the present invention,advertisements are generated and displayed to a user, wherein theadvertisements portray other individuals, including friends with whomthe user has interacted on the Internet and/or other contributors whomthe user is likely to trust or pay attention to even if the user has notdirectly interacted with them. In the context of the present disclosure,a “friend” is an individual with whom the user interacts or hasinteracted, while a “contributor” is an individual that the user may notnecessarily have interacted with. Contributors can include, for example,experts that have particular qualifications that render them trustworthyor well-respected with regard to particular subject matter, and/or anyother individuals that have an opinion or other input they wish to shareabout the subject matter. Friends and contributors are referred toherein as “subject individuals”. According to techniques describedherein, subject individuals can be portrayed in advertisements presentedto users. A subject individual need not have explicitly or implicitlyreferred an advertisement to a target user. A subject individual can beportrayed in an advertisement by including any type of representation ofthe subject individual, including representations that are visual,animated, text-based, numeric, icon-based, or of any other type; suchrepresentations can include a name, user ID, sketch, icon, handle, orany other indicator of the subject individual's identity, whether afictional identity or an actual identity.

Advertisements are selected and/or generated based, in part, on a rank,or score, for subject individuals that are relevant to the user to whomthe advertisement is targeted (the “target user”).

In various embodiments, advertisements can be selected and presented tothe target user based on any of a number of factors, taken alone or incombination. Such factors can include, for example: previousinteractions of subject individuals relevant to the target user, wheresuch previous interactions can take place directly with or in theadvertisement; and/or other actions taken by subject individualsrelevant to the target user, such as contributing related content in anenvironment other than an advertisement.

Conversely, the selection of advertisements for presentation to the usercan be viewed as a process of eliminating some advertisements from a setof candidate advertisements. For example, it may be appropriate in somecases to eliminate an advertisement if no subject individuals haveinteracted with the advertisement. Similarly, it may be appropriate insome cases to eliminate an advertisement if no friends of the targetuser have interacted or contributed with the advertisement.

Once an advertisement has been selected for display to the target user,a particular subject individual (or more than one) is selected to beportrayed in the advertisement. Selection of subject individual can bebased on various factors, including for example the target user'sinteraction history with subject individuals, a degree ofauthoritativeness of the subject individual with respect to the subjectmatter of the advertisement (based, for example, on expertise, actions,contributions, and/or contributed content), popularity of the subjectindividual, and potentially other factors.

Thus, according to various embodiments of the invention, a method isprovided for choosing which advertisement(s) to show to a user and forselecting individuals to portray in the advertisements.

In one example, a contributor can be any individual who has submitted areview or opinion, whether or not the individual has any particularexpertise on the subject of the review or opinion. In another example, acontributor can be an individual who has donated to a particular cause,so that the fact that the individual has donated may potentiallyinfluence other users to donate to the same cause. In general, thecontributor can be any individual whose action, comment, submission, orother contribution might potentially influence the actions of otherusers, regardless of the actual merit or quality of the individual'saction, comment, submission, or other contribution, and regardless ofwhether the contributor has any objective expertise on the relevantsubject.

In this manner, the present invention provides a mechanism forpresenting advertisements that the target user is more likely to act on,and/or for delivering a message that is inherently more relevant orvaluable regardless of whether the target user acts, particularly sincethe advertisement includes a representation of a friend and/or relevantcontributor.

Accordingly, using data from interactions among users via social media,the techniques described herein allow advertising networks to improvetheir web advertising display and advertising selection processes toshow more engaging social advertising to users, and thereby increase theeffectiveness of advertising efforts.

The features and advantages described in the specification are not allinclusive and, in particular, many additional features and advantageswill be apparent to one of ordinary skill in the art in view of thedrawings, specification, and claims. Moreover, it should be noted thatthe language used in the specification has been principally selected forreadability and instructional purposes, and may not have been selectedto delineate or circumscribe the disclosed subject matter.

BRIEF DESCRIPTION OF THE DRAWINGS

The disclosed embodiments have other advantages and features which willbe more readily apparent from the detailed description, the appendedclaims, and the accompanying figures (or drawings). A brief introductionof the figures is below.

FIG. 1 illustrates a system architecture according to one embodiment.

FIG. 2 illustrates one embodiment of a computer for implementing thepresent invention according to one embodiment.

FIG. 3A illustrates a screenshot of a user interface displaying anadvertisement to a first user according to one embodiment.

FIG. 3B illustrates a screenshot of a user interface displaying theinterface after the first user has interacted with the advertisement,according to one embodiment.

FIG. 3C illustrates a screenshot of a user interface displaying theadvertiser's site as it appears after the first user has clicked throughthe advertisement, according to one embodiment.

FIG. 3D illustrates a screenshot of a user interface displaying to asecond user an advertisement portraying the first user, according to oneembodiment.

FIG. 3E illustrates a screenshot of a user interface displaying theinterface after the second user has interacted with the advertisement,according to one embodiment.

FIG. 4 is a flow diagram depicting a method for displaying anadvertisement to a user according to one embodiment

DETAILED DESCRIPTION

The figures and the following description relate to preferredembodiments by way of illustration only. It should be noted that fromthe following discussion, alternative embodiments of the structures andmethods disclosed herein will be readily recognized as viablealternatives that may be employed without departing from the principlesof what is claimable subject matter.

Reference will now be made in detail to several embodiments, examples ofwhich are illustrated in the accompanying figures. It is noted thatwherever practicable similar or like reference numbers may be used inthe figures and may indicate similar or like functionality. The figuresdepict embodiments of the disclosed system (or method) for purposes ofillustration only. One skilled in the art will readily recognize fromthe following description that alternative embodiments of the structuresand methods illustrated herein may be employed without departing fromthe principles described herein.

System Architecture

FIG. 1 is a depiction of a system architecture and process flowaccording to one embodiment. The system comprises a client 110 and aserver 100 which communicate with one another via the network 105. Theserver 100 comprises a log database 115, log analysis engine 120, userscore database 125, response database 130, rank database 135,interaction database 140, friend rank analysis engine 145, advertisement(“ad”) database 150, ad rank computation and selection engine 155, andan interaction receiving engine 165.

In one embodiment, the server 100 is implemented as server programexecuting on one or more server-class computers comprising a CPU,memory, network interface, peripheral interfaces, and other well knowncomponents. If more than one computer is present, they arecommunicatively coupled together. The computers themselves havegenerally high performance CPUs, with 1 GB or more of memory, and 100 GBor more of disk storage. Of course, other types of computers can beused, and it is expected that as more powerful computers are developedin the future, they can be configured in accordance with the teachingshere. The functionality implemented by any of the elements can beprovided from computer program products that are stored in tangiblecomputer readable storage mediums (e.g., RAM, hard disk, oroptical/magnetic media), or by equivalent implementations in hardwareand/or firmware. Alternatively, the server 100 can be implemented indedicated hardware, using custom-designed circuitry to implement thelogic of the operations described herein.

FIG. 2 illustrates one embodiment of a computer on which the server 100can be implemented. Illustrated are at least one processor 202 coupledto a chipset 204. Also coupled to the chipset 204 are a memory 206, astorage device 208, a keyboard 210, a graphics adapter 212, a pointingdevice 214, and a network adapter 216. A display 218 is coupled to thegraphics adapter 212. In one embodiment, the functionality of thechipset 204 is provided by a memory controller hub 220 and an I/Ocontroller hub 222. In another embodiment, the memory 206 is coupleddirectly to the processor 202 instead of the chipset 204.

The storage device 208 is any device capable of holding data, forexample, a hard drive, compact disk read-only memory (CD-ROM), DVD, or asolid-state memory device. The memory 206 holds instructions and dataused by the processor 202. The pointing device 214 may be a mouse, trackball, or other type of pointing device, and is used in combination withthe keyboard 210 to input data into the computer 200. The graphicsadapter 212 displays images and other information on the display 218.The network adapter 216 couples the computer 200 to a local or wide areanetwork.

As is known in the art, a computer 200 can have different and/or othercomponents than those shown in FIG. 2. In addition, the computer 200 canlack certain illustrated components. In one embodiment, a computer 200lacks a keyboard 210, pointing device 214, graphics adapter 212, and/ordisplay 218. Moreover, the storage device 208 can be local and/or remotefrom the computer 200 (such as embodied within a storage area network(SAN)).

As is known in the art, the computer 200 is adapted to execute computerprogram engines (or modules) for providing functionality describedherein. As used herein, the term “engine” refers to computer programlogic, running on the computer 200, utilized to provide the specifiedfunctionality. Thus, an engine can be implemented in hardware, firmware,and/or software. In one embodiment, program engines, such as the loganalysis engine 120, friend rank analysis engine 145, ad rankcomputation and selection engine 155 and interaction receiving engine165 are stored on the storage device 208, loaded into the memory 206,and executed by the processor 202.

Embodiments of the entities described herein can include other and/ordifferent engines than the ones described here. In addition, thefunctionality attributed to the engines can be performed by other ordifferent engines in other embodiments. Moreover, this descriptionoccasionally omits the term “engine” for purposes of clarity andconvenience.

In one embodiment, the client 110 is a browser running on a computingdevice. The browser can be any browser known in the art, for example,Microsoft Internet Explorer™ or Mozilla Firefox™. The computing deviceis any computing device, such as a personal computer, a notebookcomputer, or a mobile device such as a smart phone or personal digitalassistant. For simplicity and ease of discussion, only one client 110 isshown. It is noted however, that the disclosed configuration functionswith numerous clients 110 communicating with the server 100. The network105 is any network, wired or wireless known in the art.

The log database 115 stores user histories including representations ofusers' interactions on the Internet. Interactions can includeinteractions with other users as well as interactions with applications.Examples of interactions with applications include running a searchquery at a search engine, making a purchase at an on-line retailer,and/or interactions related to an advertisement. Examples ofinteractions related to an advertisement include actions before andafter viewing an advertisement, such as: the history of the user'sbrowser that is being sent an advertisement, the history of the user'sbrowser having received an advertisement, the user interacting with anadvertisement through mouse-over or click events, and post-clickactivity on web pages, such as filling out a form, making a purchase, orinstalling an application. The log database 115 is populated by theinteraction receiving engine 165, which reviews traffic from the user atthe client 110 for interactions with contributors. Data in the logdatabase 115 can in turn be used to populate other databases in thesystem.

The log database 115 can store representations of interactions that takeplace in the context of an advertisement, as well as those that takeplace in other contexts. As an example, the log database 115 can store arepresentation of a user's interaction with a website, such as forexample a review that a user A has submitted to a website or aquestionnaire that user A has answered. Information that was recorded inconnection with the submitted review or questionnaire response can thenbe displayed as part of an advertisement that is presented to anotheruser B, whether or not user B has interacted with user A, and whether ornot the two users have a relationship with each other.

As another example, the log database 115 can store information that isgenerated in connection with an application, such as a “share a mood”application. This information may correspond to information that mightalso be collected via a user's interaction with an advertisement.

Accordingly, data in the log database 115 can be collected based on userinteraction with advertisements, and/or from other types of interactionsand/or data sources. When collected from non-advertisement-basedsources, the data may or may not be similar to information collectedfrom advertisement-based sources. Regardless of the source of data inthe log database 115, the data can be provided to users who have had aninteraction with the user from whom the data was collected.Alternatively, in some embodiments, the data may be provided to anyuser, for example via the web, regardless of whether the recipient ofthe data has had an interaction with the user from whom the data wascollected. In one embodiment, the determination as to how the datashould be made available is dependent on the preferences of the userfrom whom the data was collected. In other embodiments, thedetermination can be made based on any of a number of factors.

The log analysis engine 120 determines a score for each user, s(U). Inone embodiment, this score is an aggregate of the user's behavior inresponse to interactions that have been logged in the log database 115.For example, the score for a user can indicate how likely the user is toclick on a social advertisement, wherein a social advertisement is onethat portrays either i) a friend of the user from a social network; orii) a contributor with regard to subject matter of the advertisement.

In one embodiment, the user's score is determined from the combinationof at least two groups of measurements. The first group includes summarystatistics of how a particular user responds to social advertisements.Specifically, in one embodiment, the first group of statistics caninclude, for example:

-   -   (i) # of impressions of social advertisements shown to user,        across all friends, over a pre-determined time period of N days;    -   (ii) # of “interactions” generated by social advertisements for        impressions of (i);    -   (iii) # of clicks to an advertiser landing page for impressions        of (i);    -   (iv) # of actions after the landing page for impressions of (i);    -   (v) interaction rate computed from (i) and (ii);    -   (vi) clickthrough rate computed from (i) and (iii);    -   (vii) conversion rate computed from (i) and (iv).

The second group includes summary statistics of how all users respond tosocial advertisements. Specifically, in one embodiment, the second groupof statistics can include, for example:

-   -   (i)′ # of impressions of social advertisements shown to all        users, across all friends, over a pre-determined time period of        N days;    -   (ii)′ # of “interactions” generated by social advertisements for        impressions of (i);    -   (iii)′ # of clicks to an advertiser landing page for impressions        of (i); (iv)′ # of actions after the landing page for        impressions of (i);    -   (v)′ interaction rate computed from (i) and (ii);    -   (vi)′ clickthrough rate computed from (i) and (iii);    -   (vii)′ conversion rate computed from (i) and (iv).

In one embodiment, the user's score is a function of either the ratio ofthe user's interaction rate, v, to all users' interactions rate, v′; theuser's clickthrough rate, vi, to all users' clickthrough rate, vi′; orthe user's conversion rate, vii, to all users' conversation rate, vii′.Which of these ratios is used depends on the method of selling theadvertisements. The interactions rate, clickthrough rate and conversionrate shown here as components of the determination of a user score areconventional measurements used to price advertising on the Internet. Theinteraction rate is based on the number views of an advertisement. Theclickthrough rate is based on the number clicks on an advertisement andthe conversion rate is based on the number of purchases or other desiredaction the user undertakes after clicking on an advertisement.

In various embodiments, for advertisements that are sold per impressionor per interaction, the user score is based on the interactions, v, foradvertisements sold per click, the user score is based on theclickthrough rate, vi, and for advertisements sold per action, the userscore is based on the conversion rate, vii. The function applied to theratio can be, for example, the identity function or a sigmoid function.

Scores for users are stored in the user score database 125.Determination of user scores by the log analysis engine 120 may occurasynchronously from the choosing and displaying of an advertisement to auser. User scores can be updated, for example, at predeterminedintervals, such once a day, once a week, or once a month.

It is noted that there may be instances in which there is not enoughinformation known about a particular user for a user score to be a validpredictor. In such an instance any probabilistic technique can beemployed, such as Gibbs sampling, which considers the user score to be arandom variable.

The response database 130 stores responses to advertisements and/orother forms of contributions or input relevant to the subject matter ofadvertisements. Such responses and other input can be received fromfriends and/or from other individuals (referred to herein as“contributors”). A friend is any individual with which the user has hadan interaction on the Internet, while a contributor may be anyindividual regardless of whether the user has had an interaction withthe individual.

For example, friends can include individuals for whom the user has emailaddresses in an online address book. Online address books includeaddress books at email applications such as Yahoo! Mail™ and GMail™.Online address books also include address books stored at websites fromwhich a user sends links to other users. An example is Kodak PictureGallery™. Friends can also include other individuals that the user hasdesignated as a friend in a social network such as Facebook™ andMySpace™.

The response database 130 may assume any number of forms, such as arelational database, a memory-based key-value pair storage system, orflat file format for rapid lookup. In one embodiment, a memory key-valuesystem is loaded with a set of flat files built from a relationaldatabase of interactions.

The interaction database 140 stores metadata about interactions betweena user and the user's friends. This metadata can be used, for example,in determining an interaction score that is used to determine ranks forthe user's friends. In one embodiment, metadata for a given interactionincludes such information as: the social media site at which theinteraction occurred; the application via which the interactionoccurred; the publisher of the application, if applicable; the type ofinteraction; what the interaction was; the user(s) involved; date andtime of the interaction; and how many recipients there were of theinteraction. In one embodiment, metadata stored in the interactiondatabase 140 for a given interaction is stored in a uniform format sothat the entries are comparable across the various contexts in whichinteractions occur on the Internet.

The friend rank analysis engine 145 computes the ranks of a user'sfriends. In one embodiment, this analysis comprises determining aninteraction score based on data from the interaction database 140 andthereby determining a rank for each of the user's friends, to be storedin the rank database 135. This rank is a statistical indication of howmuch more likely a user is to click on a social advertisement given thatit indicates the advertisement is directed from a specific friend. Inone embodiment, this rank is determined using weighted sums of counts ofinteraction data using Formula (I).

$\begin{matrix}{{r\left( {U,F} \right)} = \frac{\sum_{i = 1}^{n}{w_{i}{c_{i}\left( {U,F} \right)}}}{\sum_{x}{\sum_{i = 1}^{n}{w_{i}{c_{i}\left( {U,x} \right)}}}}} & (I)\end{matrix}$

wherein: c_(i)(U,F) is a count of one type of interaction between agiven user, U, and a given friend, F, n=number of different types ofinteractions, x is any one of the user's friends, and w_(i) is theweight given to each type of interaction. Friend rank is described infurther detail in co-pending U.S. Utility patent application Ser. No.12/277,237 for “Ranking Interactions Between Users on the Internet”,filed Nov. 24, 2008, which is incorporated herein by reference.

Interaction types include various mechanisms by which a user caninteract with his or her friends. Examples including a user visitinganother user's page within a social network or wedding planning site,visiting the blog of a friend, viewing photos shared by a friend at aphoto sharing site, explicit hyperlinking of one user to another user'spage, explicit actions by one user with another user enabled by socialnetworks and social applications, or the like. In many cases,advertising networks may observe these interactions with an HTTP_REFERERuniform resource locator (“URL”) attribute, as is available when servingadvertisements to users.

Additional interaction types include gifts exchanged between the userand the user's friends using a social network's “gifting applications,”messages sent, invitations, interactions between a user and the user'sfriends via social advertisements, news feed clicks and participation bythe user in other social media applications. Examples of interactionswithin a social network include updating a map on the user's page to adda recent trip, a user going into a drink-sending application, choosing adrink, choosing a friend, adding a message, and sending the friend thatdrink. Interactions between users may be synchronous or asynchronous.

In one embodiment, each interaction type is given a weight, w_(i). Forexample, a message and an invitation might have a weight of 0.1, thesending of a gift using the gift application of the social network mighthave a weight of 0.2, and an interaction via a social advertisementmight have a weight of 0.5. Other weights might be applied to othertypes of interactions, including interactions that may take placebetween users who do not know each other.

The resulting friend ranks are stored in the rank database 135. Thefriend rank computed by the friend rank analysis engine 145 may operateasynchronously from the process of choosing and displaying anadvertisement to a user. The friend rank may be pre-computed atpre-determined intervals (such as, for example, once every 24 hours,once a week, or once a month) or computed in real time from sufficientstatistics.

In some embodiments, the present invention is adapted to operate incontexts where an individual presented in an advertisement is somecontributor whose opinion and/or actions may carry greater relevancethan would the opinion of an ordinary user, even to those who do notpersonally know the contributor. A contributor can be an individualhaving particular expertise, or can be anyone who has provided anopinion, submitted a review, or performed some other action with respectto the subject matter of interest. Since the user would not necessarilyhave had any direct interactions with such a contributor, a rank can bedeveloped based on some other mechanism, such as based on an overallassessment of the quality of the contributor's reviews or the overallvalue of his or her credentials. This rank is referred to as acontributor rank. Friend rank and contributor rank are referred toherein collectively as “subject individual rank” (or simply “rank”), andare stored in the rank database 135; friends and contributors arereferred to herein collectively as “subject individuals”.

Accordingly, in one embodiment, rank database 135 can include friendranks as well as contributor ranks, where friend ranks are derived basedon direct interactions between the friend and the user, and contributorranks are obtained via other means, such as (for example) an indicationof the popularity of the contributor. These contributor ranks can beobtained from any source 146; for example, contributor ranks forcontributors can be obtained from an API provided by a social mediawebsite that provides an indication as to how many followers thecontributor has, or some other indication of the relative popularity ortrustworthiness of the individual. Such API's are available for mostsocial media websites. In one embodiment, data from the log analysisengine 120 is used by the contributor rank source 146 to generatecontributor ranks.

Additionally or alternatively, contributor ranks can be determined basedon the relative performance of advertisements containing thecontributor's identity and/or contributed content; this assessment canbe made, for example, using data from the log analysis engine to createinternal contributor rank sources. Such internal sources may measure,for example, aggregate click-through rate for advertisements portrayingthe contributor and/or contributed content, aggregate ratings of thecontributor's content, number of comments about the contributor'scontent, and/or any other methods of evaluating the contributor and/orcontributed content. Performance and favorability statistics can also begathered in other contexts, such as when the contributor and/orcontributed content are displayed in environments other than directly inan advertisement, such as a landing page, widget, email message, orother content distribution construct.

In one embodiment, friend ranks may differ from one user to another,even for the same subject individual; for example, a subjectindividual's friend rank may be higher for user A than for user B, ifthe subject individual has had more interactions with user A than touser B. In one embodiment, a contributor rank for a given subjectindividual at a given time is applicable to all users (although it maychange over time); for example, a contributor rank may be based on anoverall assessment of the subject individual's contributed content,based on comments and/or ratings submitted by the general public.

Thus, in one embodiment, the system of the present invention obtainsfriend ranks for friends (i.e., individuals with whom the user has hadinteractions) based on the nature and degree of such interactions. Asdescribed above, for those individuals with whom the user has not hadinteractions (i.e., contributors), the system of the present inventionobtains contributor ranks based on some other measure, which preferablyreflects the degree of the individual's authoritativeness (based onexpertise, experience, and/or other qualifications) with respect to thesubject matter of an advertisement.

In one embodiment, friend ranks and contributor ranks are normalized sothat they can be meaningfully compared with one another. Alternatively,if friend ranks are not available for some subset of candidateadvertisements, contributor ranks can be used, ignoring any friend ranksthat may only be available for some of the candidate advertisements.

The advertisement database 150 stores advertisements that canpotentially be displayed to users. Advertisements may be displayed to auser when the user visits a website on the Internet. Alternatively, theadvertisement can be sent to a user electronically, such as via email,instant message, telephone call, via a social network, or the like.Additionally or alternatively, messages can be sent using a socialmessage utility such as Twitter™.

The ad rank computation and selection engine 155 determines ranks ofadvertisements for a particular user; these ranks are referred to as“AdRanks”. In one embodiment, this determination includes a computationinvolving the eCPM, user score, and aggregated subject individual ranks.A subject individual rank may be a friend rank for a friend of the user.Ranks can also, in one embodiment, include contributor ranks forindividuals whose authoritativeness (including expertise, experience,and/or other qualifications) are relevant to the advertisement; forexample, contributor rank can represent an overall assessment of thequality of an individual's reviews or the overall value of his or hercredentials. In one embodiment, the aggregated rank is an aggregationincluding both friend rank(s) and contributor rank(s).

For example, ad rank can be computed as:

Ad Rank=eCPM*s(U)*aggregated ranks for subject individuals

where s(U) represents the user score (also referred to as qualityscore).

The following is an example of the application of the above-describedtechniques. Rank values are shown for three subject individuals, who arefriends F1, F2, F3 of a user U1, based on the friends' responses toadvertisements A1 and A2.

User Subject individual Ad Rank U1 F1 A1 1.5 U1 F2 A1 3.2 U1 F1 A2 1.6U1 F3 A2 0.9

The above values can be aggregated as follows, to generate AdRank valuesfor each advertisement:

User Subject individuals Ad AdRank(A) U1 F1, F2 A1 Bid eCPM(A1) X f(1.5,3.2) U1 F1, F3 A2 Bid eCPM(A2) X f(1.6, 0.9)

That is, given friend rank data for specific response advertisementsfrom friends, the AdRanks for specific advertisements can be computedfrom the individual responses using a combinator, f. This combinator canbe the maximum value, geometric mean, arithmetic mean, or the like.Given such a combinatory function and subject individual ranks betweenusers, AdRanks are developed. These AdRanks can then be used in eCPMauctions to determine which advertisement to show.

In one embodiment, the advertisement with the highest AdRank as computedby the above-described process is displayed (or otherwise output) to theuser at the client 110. In another embodiment, some set ofadvertisements have AdRank scores exceeding a predefined threshold areidentified, and one of the identified advertisements is selected fordisplay (for example, based on a predefined rotation, random selection,ranking within the set of identified advertisements, or the like).Interactions that result from the user being displayed in anadvertisement are logged by the interaction receiving engine 165.

In some embodiments, multiple advertisements may be displayed.Accordingly, some advertisements may be displayed more prominently thanothers, based (at least in part) on the relative AdRanks of theadvertisements.

As described above, in one embodiment, the system of the presentinvention is able to compare advertisements portraying friends(individuals with whom the user has had an interaction) withadvertisements portraying contributors (individuals with whom the userhas not necessarily had an interaction), and to generate comparativeranks for each. The rank for a contributor can be determined based onthe degree to which the contributor is considered authoritative withrespect to the particular subject matter of the advertisement.

Extending the example above, suppose subject individual Cl is acontributor, with a high degree of authoritativeness relevant to thesubject matter of advertisement A1. Then, ranks might be determined asfollows:

User Subject individual Ad Rank U1 F1 A1 1.5 U1 F2 A1 3.2 U1 F1 A2 1.6U1 F3 A2 0.9 U1 C1 A1 5.0 U1 C1 A2 0.0

Note that in this example, the authoritativeness of individual Cl isconsidered highly relevant for advertisement A1 but not relevant foradvertisement A2. For example, A2 may be a subjective advertisement suchas a “mood ad”, wherein the advertisement portrays the mood of thefriend; in such a case the mood of individual Cl would not be relevantto user U1, since user U1 does not know individual Cl. Accordingly, therank of Cl with respect to advertisement A1 is assigned the relativelyhigh value of 5.0, while the rank of Cl with respect to advertisement A1is assigned a value of zero.

The above values can be aggregated as follows, to generate AdRank valuesfor each advertisement:

User Subject individuals Ad AdRank(A) U1 F1, F2, C1 A1 Bid eCPM(A1) Xf(1.5, 3.2, 5.0) U1 F1, F3, C1 A2 Bid eCPM(A2) X f(1.6, 0.9, 0.0)

In one embodiment, some set of candidate advertisements is available,and the system of the present invention selects an advertisement fromthe set of candidates. For example, in response to a client's 110request for an advertisement, five candidate advertisements might beidentified (based, for example, or certain demographic and/or geographiccharacteristics of the user associated with the client 110). Some ofthese candidate advertisements may be designated as “socialadvertisements” that only include friends, meaning that they will onlybe shown if a friend of the user has previously interacted with anequivalent advertisement. Thus, if no friends have interacted with acandidate (as determined based on data from the response database 130),that candidate is eliminated as a potential advertisement to be shown.Of those advertisements that remain, the system of the present inventiondetermines which advertisement to show, and which friend to portray inthe advertisement, based on the ad ranking mechanism described above. Arepresentation of the selected friend is then inserted in theadvertisement, and the advertisement is transmitted to the client 110for display to the user. Alternatively, some candidate advertisementsmay be designated as “social advertisements” that may include all typesof subject individuals, whether they are friends or not. In this case,the candidate advertisement may be considered for display to any user,ignoring other targeting and ad parameters, as long as there is at leastone individual who has contributed content pertaining to the candidateadvertisement (as determined based on data from the response database130).

Process Flow

Referring now also to FIG. 4, there is shown a flow diagram depicting amethod for displaying an advertisement to a target user according to oneembodiment. A target user visits 401 a website and the browser at theclient 110 requests 402 an advertisement. The ad rank computation andselection engine 155 receives the request and in turn, and obtains 403the target user's overall score s(U) from the user scores database 125as well as subject individual ranks, which may include contributor ranksand/or friend ranks for the target user's friends from the friend rankdatabase 135. The ad rank computation and selection engine 155 alsoobtains 404 advertisements from the advertisement database 150. Usingthe mechanism described previously, the ad rank computation andselection engine 155 selects 405 an advertisement (or advertisements)for display. If the subject individual (a friend or contributor) is notalready depicted in the advertisement, he or she can be inserted 409 inthe advertisement.

In one embodiment, insertion 409 of the subject individual is performedas follows. Each advertisement has at least one placeholder location inwhich the representation of the subject individual can be inserted. Theplaceholder location can be designated for a picture, name, animation,or other identifier. When the advertisement is rendered as HTML to besent to the client 110, a representation of the subject individual isinserted at the location of the placeholder. One skilled in the art willrecognize that many other mechanisms for inserting the subjectindividual's representation can be used, including for example insertionvia Adobe™ Flash™ or some other multimedia software application.Alternatively, advertisements can be pre-rendered in static form, as afile in JPG, GIF, PNG or other image format, to include the subjectindividual along with other advertising content.

In one embodiment, the picture, name, animation or other representationof the subject individual is obtained from a database (not shown)containing such information for all potential subject individuals. Thedatabase can include actual images and other content, or can includelinks (pointers), for example in the form of URLs.

The selected advertisement is then transmitted 406 to the target user'sbrowser at the client 110, which displays 407 the advertisement.

As discussed above, in one embodiment, the displayed advertisement mayportray any subject individual, including a friend of the target user,or any other individual with whom the friend has interacted, for examplein the context of a social media application (which may or may not bethe same social media application in which the advertisement is beingpresented). In another embodiment, the subject individual portrayed inan advertisement may be an individual that the target user has notnecessarily interacted with; the individual in the advertisement may bea contributor or other individual whose opinion, expertise, or actionmay be relevant to the subject matter of the advertisement. In thismanner, effectiveness of the advertisement is improved, because thetarget user is more likely to pay attention to and/or trust the contentof the advertisement when the advertisement includes a portrayal of afriend, contributor, and/or other trusted individual. The target user'sinteraction with the advertisement is logged 408 at the interactionreceiving engine 165.

Example User Interfaces and Interactions

Referring now to FIG. 3A, there is shown a screenshot 300 of a userinterface displaying an advertisement 301 to a first user according toone embodiment. The advertisement invites the first user (a subjectindividual) to respond to the question about how the first user isfeeling today, by selecting among icons 302A-D. The first user choosesmood icon 302B as a response and that response is transmitted to thesystem and stored in the log database 115.

Referring now to FIG. 3B, there is shown a screenshot 310 of a userinterface, according to one embodiment, displaying the interface afterthe first user has interacted with the advertisement 301. Theadvertisement 301 now reflects the first user's choice of mood andinvites the first user to click through the advertisement (by clickingon button 311) to access the advertiser's website. The first user'sinteraction with the advertisement 301, such as clicking on button 311,is stored in the log database 115.

Referring now to FIG. 3C, there is shown a screenshot 320 of a userinterface, according to one embodiment, displaying the advertiser'swebsite 321 as it appears after the first user has clicked on button 311in the advertisement 301 of FIG. 3B. The first user's interactions withthe advertiser's website 321, including for example, purchases, arestored in the log database 115.

As described above, the first user's interactions with the advertisement301 can be used in the generation and presentation of an advertisementfor a second user, so that the first user becomes a subject individualportrayed in the advertisement shown to the second user. Referring nowto FIG. 3D, there is shown a screenshot 330 of a user interface,according to one embodiment, displaying to a second user anadvertisement 331 including a portrayal, or representation 332, of thefirst user. In the example of FIG. 3D, representation 322 is aphotograph; however, one skilled in the art will recognize that therepresentation 332 can be a name, user ID, sketch, icon, handle, or anyother indicator of the first user's identity, whether a fictionalidentity or an actual identity. The representation 332 can be visual,animated, text-based, numeric, icon-based, or of any other type.

In one embodiment, a screenshot 330 such as shown in FIG. 3D can begenerated according to the process flow described above in connectionwith FIGS. 1 and 4. Thus, prior to displaying the advertisement 331 inFIG. D, the system of the present invention determines an advertisementto display and selects a subject individual (friend or contributor) toportray in the advertisement. In this example, the subject individualshown in the advertisement 331 is the first user (i.e., the user whointeracted with the advertisement 301 shown in FIG. 3A), as this firstuser has been identified as a friend of the second user.

In this example, the advertisement 331 shown in FIG. 3D informs thesecond user how the first user is feeling, by including a representation332 of the first user along with an icon 333 corresponding to the moodicon 102 selected by the first user in FIG. 3A. The second user is theninvited to select an icon 302A-D that illustrates the second user'smood. When the second user does so, by clicking on icon 302B, theresponse is stored in the log database 115.

Referring now to FIG. 3E, there is shown a screenshot 340 of a userinterface, according to one embodiment, displaying the interface afterthe second user has interacted with the advertisement 331. Theadvertisement 331 now reflects the first user's choice of mood andinvites the second user to click through the advertisement (by clickingon button 311) to access the advertiser's website. The second user'sinteraction with the advertisement 331, such as clicking on button 311,is stored in the log database 115.

Referring again to FIG. 3C, there is shown a screenshot 320 of a userinterface, according to one embodiment, displaying the advertiser'swebsite 321 as it appears after the second user has clicked on button311 in the advertisement 331 of FIG. 3E. The second user's interactionswith the advertiser's website 321, including for example, purchases, arestored in the log database 115.

In the above description, for illustrative purposes, advertisements aredepicted as visual components of web pages. However, one skilled in theart will recognize that advertisements selected and presented inconnection with the present invention can take any form, includingvisual, auditory, text-based, or any combination thereof. For example,and without limitation, advertisements can be animations, audiomessages, text messages, email messages, multi-media messages, or thelike. Advertisements may or may not conform to accepted standards suchas those promulgated by the Internet Architecture Board (IAB), and maybe static or dynamic in size.

Broadcasting User Interactions

In one embodiment, the interactions of a user (i.e., a subjectindividual) with an advertisement are made publicly available, forexample via an advertisement that is broadcast via the web or by anyother communications medium. Thus, an advertisement can be broadcastthat includes a representation (such as a photograph, name, or otheridentifier) of a subject individual who has interacted with the sameadvertisement, or who has interacted with another advertisement. Inanother embodiment, the broadcast advertisement can include arepresentation of a user (i.e., a subject individual) who has otherwisecontributed an opinion or response relevant to the subject matter of theadvertisement, such as by submitting a review or answering aquestionnaire. The advertisement can be broadcast to the general public,or to a selected group of individuals based on some characteristic (suchas demographics, geography, subject matter of interest, website visited,and the like). The determination of which users should receive theadvertisement can be made based on any parameters or characteristics,including for example a computed affinity or similarity between thesubject individual and the user being presented the advertisement. Suchan affinity or similarity can be used as a basis for presenting theadvertisement to a user even if that user does not necessarily know thesubject individual.

An advertisement shown in such an embodiment would resemble theadvertisement 311 depicted in FIG. 3D, where the representation 332portrays a subject individual who has interacted with the sameadvertisement, or who has interacted with another advertisement. Here,however, the advertisement 311 is broadcast to the general public or toa selected group of individuals based on some characteristic, regardlessof whether or not the target individuals personally know (or haveinteracted with) the subject individual. In this example, previous tobroadcasting this advertisement 311, the subject individual portrayed inthe representation 332 has interacted with this or another advertisementto indicate that he is in a certain mood, designated by the icon 302B.

In the above description, the invention has been described in thecontext of an embodiment wherein responses of friends and othercontributors are considered, and wherein friends and/or othercontributors can be portrayed in advertisements to a target user. Oneskilled in the art will recognize that other embodiments can beimplemented, including for example an embodiment where only theresponses of friends are considered, and only friends of the target userare eligible to be presented in advertisements.

Numerous specific details have been set forth herein to provide athorough understanding of the embodiments. It will be understood bythose skilled in the art, however, that the embodiments may be practicedwithout these specific details. In other instances, well-knownoperations, components and circuits have not been described in detail soas not to obscure the embodiments. It can be appreciated that thespecific structural and functional details disclosed herein may berepresentative and do not necessarily limit the scope of theembodiments.

In addition, some portions of the detailed description, such as theprocesses described in reference to FIG. 1, are presented in terms ofalgorithms and symbolic representations of operations on data bitswithin a computer memory, such as memory 206. These algorithmicdescriptions and representations are the means used by those skilled inthe data processing arts to most effectively convey the substance oftheir work to others skilled in the art. An algorithm is here, andgenerally, conceived to be a self-consistent sequence of processingsteps (instructions) that, when executed by a processer such asprocessor 202, lead to a desired result. The steps are those requiringphysical manipulations of physical quantities. Usually, though notnecessarily, these quantities take the form of electrical, magnetic oroptical signals capable of being stored, transferred, combined, comparedand otherwise manipulated. It is convenient at times, principally forreasons of common usage, to refer to these signals as bits, values,elements, symbols, characters, terms, numbers, or the like. Furthermore,it is also convenient at times, to refer to certain arrangements ofsteps requiring physical manipulations of physical quantities as modulesor code devices, without loss of generality.

Further, the features and advantages described in the specificationprovide a beneficial use to those making use of a system and a method asdescribed in embodiments herein. For example, a user is providedmechanisms, e.g., by receiving and/or transmitting control signals, tocontrol access to particular information as described herein. Further,these benefits accrue regardless of whether all or portions ofcomponents, e.g., server systems, to support their functionality arelocated locally or remotely relative to the user.

Some embodiments may be described using the expression “coupled” and“connected” along with their derivatives. It should be understood thatthese terms are not intended as synonyms for each other. For example,some embodiments may be described using the term “connected” to indicatethat two or more elements are in direct physical or electrical contactwith each other. In another example, some embodiments may be describedusing the term “coupled” to indicate that two or more elements are indirect physical or electrical contact. The term “coupled,” however, mayalso mean that two or more elements are not in direct contact with eachother, but yet still co-operate or interact with each other. Theembodiments are not limited in this context.

Unless specifically stated otherwise, it may be appreciated that termssuch as “processing,” “computing,” “calculating,” “determining,” or thelike, refer to the action and/or processes of a computer or computingsystem, or similar electronic computing device, that manipulates and/ortransforms data represented as physical quantities (e.g., electronic)within the computing system's registers and/or memories into other datasimilarly represented as physical quantities within the computingsystem's memories, registers or other such information storage,transmission or display devices. The embodiments are not limited in thiscontext.

As used herein any reference to “one embodiment” or “an embodiment”means that a particular element, feature, structure, or characteristicdescribed in connection with the embodiment is included in at least oneembodiment. The appearances of the phrase “in one embodiment” in variousplaces in the specification are not necessarily all referring to thesame embodiment.

Upon reading this disclosure, those of skill in the art will appreciatestill additional alternative systems and methods for targetedadvertising using data captured by social networking applications inaccordance with the disclosed principles herein. Thus, while particularembodiments and applications have been illustrated and described, it isto be understood that the embodiments are not limited to the preciseconstruction and components disclosed herein and that variousmodifications, changes and variations which will be apparent to thoseskilled in the art may be made in the arrangement, operation and detailsof the method and apparatus disclosed herein without departing from thespirit and scope of the disclosure and appended additional claimablesubject matter.

1-38. (canceled)
 39. A computer-implemented method for selecting andpresenting one or more advertisements to a user, comprising: receiving,via an interaction receiving engine, and recording, at a server, one ormore indications of advertisement interactions, the one or moreindications of advertisement interactions being received input at aclient device associated with the user and indicative of activitybetween the client device and one or more presented advertisements thatare displayed on the client device; receiving and storing, at aninteraction database, metadata corresponding to one or more indicationsof social network interactions occurring between the client deviceassociated with the user and at least one interacting subject individualusing an Internet-based social network, wherein the metadatacorresponding to each of the one or more indications of social networkinteractions is stored in a uniform format so as to enable comparison ofthe one or more indications of social network interactions to which themetadata corresponds; receiving, at the server from the client deviceassociated with the user, a request for the one or more presentedadvertisements to be presented to the user; for each of a plurality ofcandidate advertisements, determining, by the server, (i) at least onefriend rank comprising a metric associated with the at least oneinteracting subject individual with whom the user has interacted usingthe Internet-based social network, wherein the at least one friend rankis determined at least in part by the received and stored metadata and(ii) at least one contributor rank indicating relative performance ofadvertisements containing a representation of a contributing subjectindividual, the at least one contributor rank not being based on socialnetwork interactions between the contributing subject individual and theuser; for each of the plurality of candidate advertisements, aggregatingthe at least one friend rank and the at least one contributor rank, andgenerating a score for each of the plurality of candidate advertisementsbased at least in part on the aggregated at least one friend rank andthe at least one contributor rank, with the score differing from the atleast one friend rank and the at least one contributor rank; identifyinga selected advertisement set from the plurality of candidateadvertisements based at least in part on the generated scores;selecting, from the selected advertisement set, the one or morepresented advertisements based on one or more presentation criteria;comparing at least one normalized contributor rank for the one or morepresented advertisements to at least one normalized friend rank for theone or more presented advertisements; selecting, based on the comparing,a represented subject individual, the represented subject individualhaving contributed input with respect to the subject matter of the oneor more presented advertisements and having at least one recordedindication of an interaction with the one or more presentedadvertisements; determining a representation type placeholder in the oneor more presented advertisements; obtaining, from a storage database bythe server, a representation of the represented subject individualhaving a representation type that matches the representation typeplaceholder; configuring, by the server, the one or more presentedadvertisements to include the representation of the represented subjectindividual, obtained from the storage database, inserted at therepresentation type placeholder in the one or more presentedadvertisements; electronically transmitting visible indicia of the oneor more presented advertisements to a user interface of a display of theclient device associated with the user, wherein, in response toreceiving the one or more presented advertisements, the client deviceassociated with the user is configured to display, via the display ofthe client device associated with the user, the one or more presentedadvertisements that comprises the representation of the representedsubject individual and enables user interaction by the user, via theuser interface, with the visible indicia associated with the one or morepresented advertisements; and detecting, via the user interface, andstoring an interaction of the user with the visible indicia of the oneor more presented advertisements that comprises the representation ofthe represented subject individual.
 40. The method of claim 1, whereinthe one or more presentation criteria include a pre-defined rotation, arandom selection, and a ranking within the selected advertisement set.41. The method of claim 1, wherein the representation of the representedsubject individual comprises at least one selected from the groupconsisting of: a picture of the represented subject individual; a nameof the represented subject individual; an icon representing therepresented subject individual; and an identifier for the representedsubject individual.
 42. The method of claim 1, wherein identifying theselected advertisement set based at least in part on the generatedscores comprises identifying one or more selected advertisements of theselected advertisement set that each have a generated score exceeding athreshold.
 43. The method of claim 1, wherein the at least one friendrank comprises a friend rank associated with the at least oneinteracting subject individual with whom the user has interacted on anelectronically implemented social network.
 44. The method of claim 1,wherein the at least one friend rank comprises a friend rank indicatinga degree of interaction between the user and the at least oneinteracting subject individual with whom the user has interacted. 45.The method of claim 1, wherein the at least one friend rank comprises afriend rank generated responsive to at least one interaction between theat least one interacting subject individual with whom the user hasinteracted and an Internet-based component associated with the one ormore presented advertisements.
 46. The method of claim 1, wherein therepresentation of the represented subject individual comprises anindication of the represented subject individual's previous interactionwith an advertisement.
 47. The method of claim 1, wherein the one ormore presented advertisements are output as a component of a web pagedisplay.
 48. The method of claim 1, wherein at least one of the one ormore presented advertisements comprises at least one selected from thegroup consisting of: an audio advertisement; an animated advertisement;a video; a text based advertisement; a text message; an instant message;an email message; a web page; a banner; and a portion of a web page. 49.The method of claim 1, further comprising: receiving the user'sinteractions with the one or more presented advertisements; and storingthe user's interactions in a storage medium.
 50. The method of claim 1,wherein generating the score based at least in part on the aggregated atleast one friend rank and the at least one contributor rank comprisesgenerating the score based on the aggregated at least one friend rankand the at least one contributor rank combined with a user score basedon the user's history of interactions on the Internet.
 51. A computerprogram product for selecting and presenting an advertisement to a user,comprising: a computer-readable storage medium; and computer programcode, encoded on the computer-readable storage medium, for causing anelectronic device to perform the steps of: receiving, via an interactionreceiving engine, and recording, at a server, one or more indications ofadvertisement interactions, the one or more indications of advertisementinteractions being received input at a client device associated with theuser and indicative of activity between the client device and one ormore presented advertisements that are displayed on the client device;receiving and storing, at an interaction database, metadatacorresponding to one or more indications of social network interactionsoccurring between the client device associated with the user and atleast one interacting subject individual using an Internet-based socialnetwork, wherein the metadata corresponding to each of the one or moreindications of social network interactions is stored in a uniform formatso as to enable comparison of the one or more indications of socialnetwork interactions to which the metadata corresponds; receiving, atthe server from the client device associated with the user, a requestfor the one or more presented advertisements to be presented to theuser; for each of a plurality of candidate advertisements, determining,by the server, (i) at least one friend rank comprising a metricassociated with the at least one interacting subject individual withwhom the user has interacted using the Internet-based social network,wherein the at least one friend rank is determined at least in part bythe received and stored metadata and (ii) at least one contributor rankindicating relative performance of advertisements containing arepresentation of a contributing subject individual, the at least onecontributor rank not being based on social network interactions betweenthe contributing subject individual and the user; for each of theplurality of candidate advertisements, aggregating the at least onefriend rank and the at least one contributor rank, and generating ascore for each of the plurality of candidate advertisements based atleast in part on the aggregated at least one friend rank and the atleast one contributor rank, with the score differing from the at leastone friend rank and the at least one contributor rank; identifying aselected advertisement set from the plurality of candidateadvertisements based at least in part on the generated scores;selecting, from the selected advertisement set, the one or morepresented advertisements based on one or more presentation criteria;comparing at least one normalized contributor rank for the one or morepresented advertisements to at least one normalized friend rank for theone or more presented advertisements; selecting, based on the comparing,a represented subject individual, the represented subject individualhaving contributed input with respect to the subject matter of the oneor more presented advertisements and having at least one recordedindication of an interaction with the one or more presentedadvertisements; determining a representation type placeholder in the oneor more presented advertisements; obtaining, from a storage database bythe server, a representation of the represented subject individualhaving a representation type that matches the representation typeplaceholder; configuring, by the server, the one or more presentedadvertisements to include the representation of the represented subjectindividual, obtained from the storage database, inserted at therepresentation type placeholder in the one or more presentedadvertisements; electronically transmitting visible indicia of the oneor more presented advertisements to a user interface of a display of theclient device associated with the user, wherein, in response toreceiving the one or more presented advertisements, the client deviceassociated with the user is configured to display, via the display ofthe client device associated with the user, the one or more presentedadvertisements that comprise the representation of the representedsubject individual and enable user interaction by the user, via the userinterface, with the visible indicia associated with the one or morepresented advertisements; and detecting, via the user interface, andstoring an interaction of the user with the visible indicia of the oneor more presented advertisements that comprise the representation of therepresented subject individual.
 52. The computer program product ofclaim 13, wherein the one or more presentation criteria include apre-defined rotation, a random selection, and a ranking within theselected advertisement set.
 53. The computer program product of claim13, wherein the at least one friend rank comprises a friend rankassociated with the at least one interacting subject individual withwhom the user has interacted on an electronically implemented socialnetwork.
 54. The computer program product of claim 13, wherein the atleast one friend rank comprises a friend rank indicating a degree ofinteraction between the user and the at least one interacting subjectindividual with whom the user has interacted.
 55. The computer programproduct of claim 13, wherein the at least one friend rank comprises afriend rank generated responsive to at least one interaction between theat least one interacting subject individual with whom the user hasinteracted and an Internet-based component associated with theadvertisement.
 56. The computer program product of claim 13, wherein atleast one of the one or more presented advertisements comprises at leastone selected from the group consisting of: an audio advertisement; ananimated advertisement; a video; a text based advertisement; a textmessage; an instant message; an email message; a web page; a banner; anda portion of a web page.
 57. The computer program product of claim 13,comprising further computer program code for: receiving the user'sinteractions with the one or more presented advertisements; and storingthe user's interactions in a storage medium.
 58. A system for selectingand presenting an advertisement to a user, comprising: an interactionreceiving engine to receive one or more indications of advertisementinteractions; a database to record the one or more indications ofadvertisement interactions, indications of advertisement interactionsbeing received input at a client device associated with a userindicative of activity between the client device associated with theuser and one or more presented advertisements displayed on the clientdevice associated with the user; an interaction database to receive andrecord metadata corresponding to one or more indications of socialnetwork interactions occurring between the client device associated withthe user and at least one interacting subject individual using anInternet-based social network, wherein the metadata corresponding toeach of the one or more indications of social network interactions isstored in a uniform format so as to enable comparison of the one or moreindications of social network interactions to which the metadatacorresponds; a server, to receive, from the client device associatedwith the user, a request for the one or more presented advertisements tobe presented to the user; an advertisement rank computation andselection engine to: for each of a plurality of candidateadvertisements, determine (i) at least one friend rank comprising ametric associated with the at least one interacting subject individualwith whom the user has interacted using the Internet-based socialnetwork, wherein the at least one friend rank is determined at least inpart by the received and stored metadata and (ii) at least onecontributor rank indicating relative performance of advertisementscontaining a representation of a contributing subject individual, the atleast one contributor rank not being based on social networkinteractions between the contributing subject individual and the user;for each of the plurality of candidate advertisements, aggregate the atleast one friend rank and the at least one contributor rank, andgenerate a score for each of the plurality of candidate advertisementsbased at least in part on the aggregated at least one friend rank andthe at least one contributor rank, with the score differing from the atleast one friend rank and the at least one contributor rank; identify aselected advertisement set from the plurality of candidateadvertisements based at least in part on the generated scores; select,from the selected advertisement set, the one or more presentedadvertisements based on one or more presentation criteria; compare atleast one normalized contributor rank for the one or more presentedadvertisements to at least one normalized friend rank for the one ormore presented advertisements; select, based on the comparing, arepresented subject individual, the represented subject individualhaving contributed input with respect to the subject matter of the oneor more presented advertisements and having at least one recordedindication of an interaction with the one or more presentedadvertisements; determine a representation type placeholder in each ofthe one or more presented advertisements; obtain, from a storagedatabase by the server, a representation of the represented subjectindividual having a representation type that matches each of therepresentation type placeholders in the one or more presentedadvertisements; configure, by the server, the one or more presentedadvertisements to include the representation of the represented subjectindividual, obtained from the storage database, inserted at each of therepresentation type placeholders in the one or more presentedadvertisements; a transmission device to electronically transmit visibleindicia of the one or more presented advertisements to a user interfaceof a display of the client device associated with the user, wherein, inresponse to receiving the one or more presented advertisements, theclient device associated with the user is configured to display, via thedisplay, the one or more presented advertisements that comprise therepresentation of the represented subject individual; and detect, viathe user interface, and store an interaction of the user with the one ormore presented advertisements that comprise the representation of therepresented subject individual.